Arvind Narayanan

Arvind Narayanan is an Assistant Professor at Princeton's Department of Computer Science and Center for Information Technology Policy and an Affiliate Scholar at the Stanford Law School Center for Internet and Society. He studies information privacy and security, and has a side-interest in tech policy. His research has shown that data anonymization is broken in fundamental ways, for which he jointly received the 2008 Privacy Enhancing Technologies Award. He is one of the researchers behind the "Do Not Track" proposal. You can follow Arvind on Twitter at @random_walker and on Google+ here.

The Do Not Track war has raged for well over a year now. There are, broadly, two Do Not Track proposals: one chiefly backed by the ad industry, and another advanced by privacy advocates. These proposals reflect vastly different visions for Do Not Track with vastly different practical consequences.

A 1993 New Yorker cartoon famously proclaimed, "On the Internet, nobody knows you're a dog." The Web is a very different place today; you now leave countless footprints online. You log into websites. You share stuff on social networks. You search for information about yourself and your friends, family, and colleagues. And yet, in the debate about online tracking, ad networks and tracking companies would have you believe we're still in the early 90s — they regularly advance, and get away with, “anonymization” or “we don’t collect Personally Identifiable Information” as an answer to privacy concerns.

A frequent misconception of Do Not Track is that the goal is to prevent tracking by online advertisers. In fact, tracking is a much broader problem on the web, and our Do Not Track vision at Stanford, while principally aimed at "third-party" tracking, does not focus on specific industry segments. Barocas and Nissenbaum said it best:

There’s an ongoing arms race between ad blockers and websites — more and more sites either try to sneak their ads through or force users to disable ad blockers. Most previous discussions have assumed that this is a cat-and-mouse game that will escalate indefinitely. But in a new paper, accompanied by proof-of-concept code, we challenge this claim.

Online tracking: A 1-million-site measurement and analysis is the largest and most detailed measurement of online tracking to date. We measure stateful (cookie-based) and stateless (fingerprinting-based) tracking, the effect of browser privacy tools, and "cookie syncing".

This measurement is made possible by our web measurement tool OpenWPM, a mature platform that enables fully automated web crawls using a full-fledged and instrumented browser.

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"“From a technical point of view, this is Apple's ‘fault,’” Arvind Narayanan, an assistant professor of computer science at Princeton who has worked on developing Do Not Track, told me in an email. “If the API in question doesn't expose that functionality, there's nothing Google or Mozilla can do about it.”"

"It is difficult for society to work out a legal framework to differentiate between good and bad uses of this technology, says Arvind Narayanan, a computer scientist at Princeton University in New Jersey. “How do you regulate around Bitcoin without banning the technology itself?” he asks.

"“There are very good reasons why we have legal and social institutions and economic intermediaries,” said Arvind Narayanan, an assistant professor of computer science at Princeton who studies block-chain technology.

"“A couple of us and our graduate students in the computer science department have been doing and publishing research on bitcoins, and it’s been a fascinating system, bringing together cryptography, distributive systems and game theory,” Narayanan said. “Bitcoins put them together in a way the academy has never anticipated.”"

""What's unfortunate is the huge gap of information - understanding what's happening on the Web and what users know about tracking," said conference organiser and assistant Professor of Computer Science Arvind Narayanan. "We're interested in building tools by the public and for the public. We want to make transparency mutually beneficial between businesses and Web users.""

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Solutions to many pressing economic and societal challenges lie in better understanding data. New tools for analyzing disparate information sets, called Big Data, have revolutionized our ability to find signals amongst the noise. Big Data techniques hold promise for breakthroughs ranging from better health care, a cleaner environment, safer cities, and more effective marketing. Yet, privacy advocates are concerned that the same advances will upend the power relationships between government, business and individuals, and lead to prosecutorial abuse, racial or other profiling, discrimination, redlining, overcriminalization, and other restricted freedoms.

"Princeton's Arvind Narayanan and Steven Englehardt studied how all the things we do not see as users are valuable to someone on our digital trail, as our presence may be authenticated and tracked through such minutia as personalized browser settings or even our laptops' battery levels.

"While Google has used differential privacy to analyze user data from its Chrome browser, Apple is the first major tech company to adopt it more widely and publicly, said Arvind Narayanan, a computer scientist at Princeton University.

“That’s what makes this so exciting – both for the technology and for the future of privacy protection,” he explained.

In terms of challenges, Narayanan said the technology could come with extra costs.

Abstract: Behind the hype and tumult of the markets, researchers have been quietly producing a series of exciting results about Bitcoin and cryptocurrencies. In this paper we’ll explain why computer scientists should pay attention to these developments.